package com.tanhua.dubbo.api;

import cn.hutool.core.collection.CollUtil;
import com.tanhua.model.mongo.RecommendUser;
import com.tanhua.model.mongo.UserLike;
import com.tanhua.model.vo.PageResult;
import org.apache.dubbo.config.annotation.DubboService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.data.domain.Sort;
import org.springframework.data.mongodb.core.MongoTemplate;
import org.springframework.data.mongodb.core.aggregation.Aggregation;
import org.springframework.data.mongodb.core.aggregation.AggregationResults;
import org.springframework.data.mongodb.core.aggregation.TypedAggregation;
import org.springframework.data.mongodb.core.query.Criteria;
import org.springframework.data.mongodb.core.query.Query;

import java.util.List;

@DubboService
public class RecommendUserApiImpl implements RecommendUserApi {

    @Autowired
    private MongoTemplate mongoTemplate;

    /**
     * 查询今日佳人
     * @param toUserId
     * @return
     */
    @Override
    public RecommendUser queryWithMaxScore(Long toUserId) {
        //根据toUserId查询，根据评分score排序，获取第一条
        //构建Criteria
        Criteria criteria = Criteria.where("toUserId").is(toUserId);
        //构建Query
        Query query = Query.query(criteria).with(Sort.by(Sort.Order.desc("score")))
                .limit(1);
        //调用mongoTemplate查询
        return mongoTemplate.findOne(query, RecommendUser.class);
    }


    /**
     * 分页查询
     * @param page
     * @param pagesize
     * @param toUserId
     * @return
     */
    @Override
    public PageResult queryRecommendUserList(Integer page, Integer pagesize, Long toUserId) {
        //1、构建Criteria对象
        Criteria criteria = Criteria.where("toUserId").is(toUserId);
        //2.构造Query对象
        Query query = Query.query(criteria).skip((page - 1) * pagesize).limit(pagesize).with(Sort.by(Sort.Order.desc("score")));
        //3、调用mongoTemplate查询
        List<RecommendUser> list = mongoTemplate.find(query, RecommendUser.class);
        //4、构建返回值PageResult
        long count = mongoTemplate.count(query, RecommendUser.class);
        return new PageResult(page, pagesize, count, list);
    }

    /**
     * 构造条件查询佳人信息
     * @param toUserId
     * @param userId
     * @return
     */
    @Override
    public RecommendUser personalInfo(Long userId, Long toUserId) {
        Criteria criteria = Criteria.where("toUserId").is(toUserId)
                .and("userId").is(userId);
        Query query = Query.query(criteria);
        RecommendUser user = mongoTemplate.findOne(query, RecommendUser.class);
        //如果没有推荐信息，就自己构建一条
        if (user == null) {
            user = new RecommendUser();
            user.setUserId(userId);
            user.setToUserId(toUserId);
            user.setScore(99D);
        }
        return user;
    }


    /**
     * 查询探花列表，查询时需要排除喜欢和不喜欢的用户
     * 1、排除喜欢，不喜欢的用户
     * 2、随机展示
     * 3、指定数量
     */
    @Override
    public List<RecommendUser> queryCardsList(Long userId, int count) {
        //1.查询喜欢不喜欢的用户id
        Query query = Query.query(Criteria.where("userId").is(userId));
        List<UserLike> likeList = mongoTemplate.find(query, UserLike.class);
        List<Long> values = CollUtil.getFieldValues(likeList, "likeUserId", Long.class);
        //2.构造查询推荐用户的条件
        Criteria criteria = Criteria.where("toUserid").is(userId)
                .and("userId").nin(values);
        //3、使用统计函数，随机获取推荐的用户列表
        TypedAggregation<RecommendUser> newAggregation = TypedAggregation.newAggregation(RecommendUser.class,
                //指定查询条件
                Aggregation.match(criteria),
                //指定数量
                Aggregation.sample(count)
        );
        AggregationResults<RecommendUser> results = mongoTemplate.aggregate(newAggregation, RecommendUser.class);
        //4、构造返回
        return results.getMappedResults();
    }
}

